基于模糊概率符号有向图的复杂系统故障诊断  

Fault Diagnosis Based on Fuzzy Probability Signed Directed Graph in Complex System

作　　者：朱琳[1] 陈杰[1] 陈文颉[1] 邓方[1] 

机构地区：[1]北京理工大学信息科学技术学院自动控制系,北京100081

出　　处：《北京理工大学学报》2007年第11期969-973,共5页Transactions of Beijing Institute of Technology

基　　金：国家部委预研项目

摘　　要：通过分析复杂系统的故障信息传递特性,在符号有向图(SDG)中引入了状态关联概率和模糊信息,并结合面向对象技术提出了一种新的故障描述模型——模糊概率有向图.给出了基于此模型的建模方法和诊断流程.进一步引入消息节点和支路,通过连接各子实体对象的模糊概率SDG模型,构成整个复杂系统的模糊概率SDG系统.该模型能对复杂系统故障诊断中存在的复杂关联关系进行建模与故障诊断.利用该方法建立了某武器平台的故障诊断系统,实验结果表明提出的方法有效且实用.After analyzing the information transfer characteristics of large-scale complex systems, a new fault description model-fuzzy probability signed directed graph （FPSDG） was proposed by introducing the status association probability, fuzzy information and object-oriented technology in SDG. The modeling method and procedure of diagnosis is proposed. On this basis, the message node and route is introduced to connect the FPSDG of those subsystems, and then the FPSDGs model of the whole complex system constructed. The complicated association of complex system malfunction can be modeled and diagnosed by the proposed method. Finally, the fault diagnosis system of a weapon carrier is built up with the proposed method. Experimental result of this system proved the effectivity and utility of this model.

关 键 词：故障诊断 符号有向图 状态关联概率 模糊信息 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]